Falling Basins: revealing hidden faults from patterns of land subsidence from water extraction using Earth Observation data

坠落盆地：利用地球观测数据从提取水的地面沉降模式中揭示隐藏的断层

• 批准号: 2604200
• 金额: --
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2604200
• 关键词: Falling; Basins; revealing; hidden; faults

Many earthquake faults remain to be discovered around the world, sometimes because they are hidden in the landscape, covered by sediments in basins. Cities are built on these basins because they offer fertile ground for agriculture and sources of water contained within the ground. However, groundwater extraction can induce significant land subsidence. Whilst a problem for housing and water supply, it provides an important opportunity to find faults beneath the city that may pose a future earthquake risk.We can detect these faults as they preferentially control how ground water flows in the subsurface and within aquifers, and consequently exhibit a structural control on how the ground surface sinks. Using the latest Earth Observation satellites, such as Sentinel-1, this project will detect these subsidence patterns to find the hidden faults beneath major cities around the world using the technique of InSAR (Elliott, 2020). We anticipate that including horizontal as well as vertical motion will improve detection of subsidence and fault locations. This work is important because seismic hazard and hidden faults potentially affect many people in growing cities (Crowley & Elliott, 2012). Many major faults lie along the edge of mountains and basins, and accommodate the relative motion between these two tectonic domains. However, faults also form within basins as the deformation migrates through time and the fault may be hidden within the basin (Elliott et al., 2020). This research will be interdisciplinary and engage directly with disaster risk and humanitarian practitioners to tailor relevant science-based outputs for integration within disaster risk assessment and emergency scenario planning. This will therefore support the realisation of UN development goal of sustainable cities and reduced loss of life from hazards.An improved understanding of the geomechanical effects of groundwater withdrawal and the control of faults of the flow of fluids will be gained through poro-elastic modelling (Gambolati & Teatini, 2015) placing constraints on the patterns of anthropogenic land subsidence. A step change in observing spatial and temporal patterns of deformation over regional areas is now possible with satellite radar such as Sentinel-1, with accuracies better than a few millimetres per year using InSAR. This project will use these space-based measurements of differential subsidence rates to test methods that reveal these concealed faults beneath cities in actively deforming regions. It will test the hypothesis that fault detection is greatly enhanced with the use of horizontal deformation in addition to vertical rates, both through direct imagery and computer vision analysis of the observations and in numerical models of aquifer flow. By quantifying the spatial and temporal pattern of subsidence, using such data analysis techniques as Independent Component Analysis, identification of potential hidden faults within the sediments will be possible. By comparing this to predictions of surface deformation from basin-wide compaction modelling of subsidence, the faults acting as barriers or conduits to fluid flow will be detected as these will alter the first-order subsidence signal. Once identified, the locations and sizes of faults relative to exposed urban populations will be co-designed with key stakeholders to produce applied seismic hazard and risk analyses using a scenario-based approach (Hussain et al., 2020).The student will work under the supervision of Dr. John Elliott, within the Active Tectonics group of the Institute of Geophysics & Tectonics in the School of Earth & Environment at Leeds. The project will be co-supervised by Dr Mark Thomas (also in IGT, SEE) and Dr Kate Crowley (University of Edinburgh). The Institute of Geophysics & Tectonics at Leeds also hosts the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET) which provides a large group of researchers engaged in active tec

世界上仍有许多地震断层在世界范围内发现，有时是因为它们隐藏在景观中，并被盆地的沉积物覆盖。城市之所以建立在这些盆地上，是因为它们为农业和地面内的水源提供肥沃的地面。但是，地下水提取可以引起大量的土地沉降。虽然住房和供水问题，但它提供了一个重要的机会，可以在城市下方找到可能构成未来地震风险的故障。我们可以检测到这些断层，因为它们优先控制地下水在地下和含水层中的流动方式，并因此对地面表面水槽的方式表现出结构性控制。使用最新的地球观测卫星（例如Sentinel-1），该项目将使用Insar技术检测这些沉降模式，以发现世界上主要城市下的隐藏断层（Elliott，2020）。我们预计包括水平和垂直运动在内将改善对沉降和断层位置的检测。这项工作很重要，因为地震危害和隐藏缺陷可能会影响不断发展的城市中的许多人（Crowley＆Elliott，2012年）。许多主要断层沿着山脉和盆地的边缘，可容纳这两个构造域之间的相对运动。然而，随着变形随时间迁移，盆地内的断层也会形成，并且断层可能隐藏在盆地内（Elliott等，2020）。这项研究将是跨学科的，并直接参与灾难风险和人道主义从业人员，以量身定制相关的基于科学的产量，以在灾难风险评估和紧急情况计划中整合。因此，这将支持实现可持续城市的联合国发展目标，并减少危害的生命损失。对地下水撤离的地质力学影响的理解以及对流体流动的控制的控制将通过孔隙弹性建模（Gambolati＆Teatini，2015，2015）来实现，将约束限制对动态陆地的模式。现在，使用卫星雷达（如Sentinel-1）可以观察到区域区域变形的空间和时间变形的步骤变化，其精度比每年使用INSAR每年要好几毫米。该项目将使用这些基于差分沉降速率的空间测量值来测试方法，这些方法揭示了积极变形区域中城市下方的隐藏断层。它将测试以下假设：除了直接的图像和计算机视觉分析，对观测值和含水层流的数值模型中的直接图像和计算机视觉分析，除了垂直速率外，使用水平变形大大增强了故障检测。通过量化沉降的空间和时间模式，使用这样的数据分析技术（如独立的组件分析），可以识别沉积物内潜在的隐藏故障。通过将其与沉降盆地全盆地压实模型的表面变形的预测进行比较，将检测到充当流体流的障碍物或导管的断层，因为这些断层将改变一阶沉积信号。 Once identified, the locations and sizes of faults relative to exposed urban populations will be co-designed with key stakeholders to produce applied seismic hazard and risk analyses using a scenario-based approach (Hussain et al., 2020).The student will work under the supervision of Dr. John Elliott, within the Active Tectonics group of the Institute of Geophysics & Tectonics in the School of Earth & Environment at Leeds.该项目将由马克·托马斯（Mark Thomas）博士（也在IGT中）和凯特·克劳利（Kate Crowley）博士（爱丁堡大学）共同监督。利兹的地球物理学与构造学院还举办了地震，火山和构造学的观察和建模中心（彗星），该中心提供了一大批从事主动TEC的研究人员